- Title
- Monitoring and Mapping Vegetation Cover Changes in Arid and Semi-Arid Areas Using Remote Sensing Technology: A Review
- Creator
- Almalki, Raid; Khaki, Mehdi; Saco, Patricia M.; Rodriguez, Jose F.
- Relation
- Remote Sensing Vol. 14, Issue 20, no. 5143
- Publisher Link
- http://dx.doi.org/10.3390/rs14205143
- Publisher
- MDPI
- Resource Type
- journal article
- Date
- 2022
- Description
- Vegetation cover change is one of the key indicators used for monitoring environmental quality. It can accurately reflect changes in hydrology, climate, and human activities, especially in arid and semi-arid regions. The main goal of this paper is to review the remote sensing satellite sensors and the methods used for monitoring and mapping vegetation cover changes in arid and semi-arid. Arid and semi-arid lands are eco-sensitive environments with limited water resources and vegetation cover. Monitoring vegetation changes are especially important in arid and semi-arid regions due to the scarce and sensitive nature of the plant cover. Due to expected changes in vegetation cover, land productivity and biodiversity might be affected. Thus, early detection of vegetation cover changes and the assessment of their extent and severity at the local and regional scales become very important in preventing future biodiversity loss. Remote sensing data are useful for monitoring and mapping vegetation cover changes and have been used extensively for identifying, assessing, and mapping such changes in different regions. Remote sensing data, such as satellite images, can be obtained from satellite-based and aircraft-based sensors to monitor and detect vegetation cover changes. By combining remotely sensed images, e.g., from satellites and aircraft, with ground truth data, it is possible to improve the accuracy of monitoring and mapping techniques. Additionally, satellite imagery data combined with ancillary data such as slope, elevation, aspect, water bodies, and soil characteristics can detect vegetation cover changes at the species level. Using analytical methods, the data can then be used to derive vegetation indices for mapping and monitoring vegetation.
- Subject
- vegetation cover change; arid regions; remote sensing; GIS; multispectral; hyperspectral; SDG 8; Sustainable Development Goals
- Identifier
- http://hdl.handle.net/1959.13/1492312
- Identifier
- uon:53294
- Identifier
- ISSN:2072-4292
- Language
- eng
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